We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...
Abstract. The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuz...
Abstract: We define events so as to reduce the number of events and decision variables needed for modeling batchscheduling problems such as described in [Westenberger and Kallrath ...
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...